Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification.

ABSTRACT: Cancer subtypes identification is one of the critical steps toward advancing personalized anti-cancerous therapies. Accumulation of a massive amount of multi-platform omics data measured across the same set of samples provides an opportunity to look into this deadly disease from several views simultaneously. Few integrative clustering approaches are developed to capture shared information from all the views to identify cancer subtypes. However, they have certain limitations. The challenge here is identifying the most relevant feature space from each omic view and systematically integrating them. Both the steps should lead toward a global clustering solution with biological significance. In this respect, a novel multi-omics clustering algorithm named RISynG (Recursive Integration of Synergi

SUBMITTER: Madhumita 

PROVIDER: S-EPMC9482647 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature